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DBMS > AnzoGraph DB vs. Apache Doris vs. Drizzle vs. EsgynDB vs. Google Cloud Datastore

System Properties Comparison AnzoGraph DB vs. Apache Doris vs. Drizzle vs. EsgynDB vs. Google Cloud Datastore

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Doris  Xexclude from comparisonDrizzle  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAn MPP-based analytics DBMS embracing the MySQL protocolMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelGraph DBMS
RDF store
Relational DBMSRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.57
Rank#244  Overall
#113  Relational DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websitecambridgesemantics.com/­anzographdoris.apache.org
github.com/­apache/­doris
www.esgyn.cncloud.google.com/­datastore
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmgithub.com/­apache/­doris/­wikicloud.google.com/­datastore/­docs
DeveloperCambridge SemanticsApache Software Foundation, originally contributed from BaiduDrizzle project, originally started by Brian AkerEsgynGoogle
Initial release20182017200820152008
Current release2.3, January 20211.2.2, February 20237.2.4, September 2012
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++, Java
Server operating systemsLinuxLinuxFreeBSD
Linux
OS X
Linuxhosted
Data schemeSchema-free and OWL/RDFS-schema supportyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes, details here
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.yesyes infowith proprietary extensionsyesSQL-like query language (GQL)
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
MySQL client
JDBCADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
Python
JavaC
C++
Java
PHP
All languages supporting JDBC/ODBC/ADO.Net.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnoJava Stored Proceduresusing Google App Engine
Triggersnonono infohooks for callbacks inside the server can be used.noCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardinghorizontal partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusternoneMulti-source replication
Source-replica replication
Multi-source replication between multi datacentersMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingnonoyesyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityno infonot needed in graphsnoyesyesyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlAccess rights for users and rolesfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
AnzoGraph DBApache DorisDrizzleEsgynDBGoogle Cloud Datastore
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